期刊
LWT-FOOD SCIENCE AND TECHNOLOGY
卷 44, 期 10, 页码 2053-2058出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.lwt.2011.05.015
关键词
Pork; Storage time; Determination; FT-NIR spectroscopy; Classification algorithm
资金
- Natural and Science Foundation of Jiangsu Province [BK2009216]
- China Postdoctoral Science Foundation [201003559, 20090461071]
- Priority Academic Program Development of Jiangsu Higher Education Institutions
To address the rapid and nondestructive determination of pork storage time associated with its freshness, Fourier transform near infrared (FT-NIR) spectroscopy technique, with the help of classification algorithm, was attempted in this work. To investigate the effects of different linear and non-linear classification algorithms on the discrimination results, linear discriminant analysis (LDA), K-nearest neighbors (KNN), and back propagation artificial neural network (BP-ANN) were used to develop the discrimination models, respectively. The number of principal components (PCs) and other parameters were optimized by cross-validation in developing discrimination models. Experimental results showed that the performance of BP-ANN model was superior to others, and the optimal BP-ANN model was achieved when 5 PCs were included. The discrimination rates of the BP-ANN model were 99.26% and 96.21% in the training and prediction sets, respectively. The overall results sufficiently demonstrate that the FT-NIR spectroscopy technique combined with BP-ANN classification algorithm has the potential to determine pork storage time associated with its freshness. (C) 2011 Elsevier Ltd. All rights reserved.
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